Docs fixed!

package/MDAnalysis/analysis/diffusionmap.py

@@ -100,11 +100,36 @@
 approximated by the euclidean distance  between rows i and j of
 self.diffusion_space.
 
+
+.. _Distance-Matrix-tutorial:
+
+Distance Matrix tutorial
+------------------------
+
+Often a, a custom distance matrix could be useful for local
+epsilon determination or other manipulations on the diffusion
+map method. The :class:`DistanceMatrix` exists in
+:mod:`~MDAnalysis.analysis.diffusionmap` and can be passed
+as an initialization argument for :class:`DiffusionMap`.
+    >>> import MDAnalysis as mda
+    >>> import numpy as np
+    >>> import MDAnalysis.analysis.diffusionmap as diffusionmap
+    >>> from MDAnalysis.tests.datafiles import PSF, DCD
+
+Now create the distance matrix and pass it as an argument to
+:class:`DiffusionMap`.
+
+    >>> u = mda.Universe(PSF,DCD)
+    >>> dist_matrix = diffusionmap.DistanceMatrix(u, select='all')
+    >>> dist_matrix.run()
+    >>> dmap = diffusionmap.DiffusionMap(dist_matrix)
+    >>> dmap.run()
+
 Classes
 -------
 
 .. autoclass:: DiffusionMap
-.. autoclass:: DistMatrix
+.. autoclass:: DistanceMatrix
 
 References
 ----------
@@ -116,14 +141,15 @@
 Coifman, Ronald R., Lafon, Stephane Diffusion maps. Appl. Comput. Harmon.
 Anal. 21, 5–30  (2006).
 
-For more information:
+For more information
+--------------------
+
 .. [deLaPorte1]
 J. de la Porte, B. M. Herbst, W. Hereman, S. J. van der Walt.
 An Introduction to Diffusion Maps.
 
 .. [Clementi1]
-Rohrdanz, M. A, ZheA flexible ALPS/Aprun task bundler https://www.olcf.ornl.gov/kb_articles/wraprun/
-ng, W, Maggioni, M, & Clementi, C.
+Rohrdanz, M. A, Zheng, W, Maggioni, M, & Clementi, C.
 Determination of reaction coordinates via locally scaled
 diffusion map. J. Chem. Phys. 134, 124116 (2011).
 
@@ -132,7 +158,6 @@
 Debenedetti,  P. G. Nonlinear dimensionality reduction in molecular simulation:
 The diffusion map approach  Chem. Phys. Lett. 509, 1−11 (2011)
 
-
 .. If you choose the default metric, this module uses the fast QCP algorithm
 [Theobald2005]_ to calculate the root mean square distance (RMSD) between
 two coordinate sets (as implemented
@@ -155,25 +180,12 @@
 
 
 class DistanceMatrix(AnalysisBase):
-    """ Calculate the pairwise distance between each frame in a trajectory using
-        a given metric
+    """Calculate the pairwise distance between each frame in a trajectory
+    using a given metric
 
     A distance matrix can be initialized on its own and used as an
-    initialization argument in :class:`DiffusionMap`:: As an example
-
-        >>> import MDAnalysis as mda
-        >>> import numpy as np
-        >>> import MDAnalysis.analysis.diffusionmap as diffusionmap
-        >>> from MDAnalysis.tests.datafiles import PSF, DCD
-
-    Now create the distance matrix and pass it as an argument to
-    :class:`DiffusionMap`.
-
-        >>> u = mda.Universe(PSF,DCD)
-        >>> dist_matrix = diffusionmap.DistanceMatrix(u, select='all')
-        >>> dist_matrix.run()
-        >>> dmap = diffusionmap.DiffusionMap(dist_matrix)
-        >>> dmap.run()
+    initialization argument in :class:`DiffusionMap`. Refer to the
+    :ref:`Distance-Matrix-tutorial` for a demonstration.
 
     Attributes
     ----------
@@ -299,33 +311,10 @@ def __init__(self, u, epsilon=1, **kwargs):
             Specifies the method used for the choice of scale parameter in the
             diffusion map. More information in [Lafon1]_, [Ferguson1]_ and
             [Clementi1]_, Default: 1.
-
-        Keywords
-        --------
-        select: str, optional
-            Any valid selection string for
-            :meth:`~MDAnalysis.core.AtomGroup.AtomGroup.select_atoms`
-            This selection of atoms is used to calculate the RMSD between
-            different frames. Water should be excluded.
-        metric : function, optional
-            Maps two numpy arrays to a float, is positive definite and
-            symmetric. The API for a metric requires that the arrays must have
-            equal length, and that the function should have weights as an
-            optional argument. Weights give each index value its own weight for
-            the metric calculation over the entire arrays. Default: metric is
-            set to rms.rmsd().
-        cutoff : float, optional
-            Specify a given cutoff for metric values to be considered equal,
-            Default: 1EO-5
-        weights : array, optional
-            Weights to be given to coordinates for metric calculation
-        start : int, optional
-            First frame of trajectory to analyse, Default: 0
-        stop : int, optional
-            Last frame of trajectory to analyse, Default: -1
-        step : int, optional
-            Step between frames to analyse, Default: 1
-        """
+        **kwargs
+            Parameters to be passed for the initialization of a
+            :class:`DistanceMatrix`.
+            """
         if isinstance(u, Universe):
             self._dist_matrix = DistanceMatrix(u, **kwargs)
         elif isinstance(u, DistanceMatrix):